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32 SMT007 MAGAZINE I JANUARY 2026 you'll be using yourself as your test environment. Finally, set aside 10–15% for pricing strategy development, sales training, marketing, and initial customer acquisition support. Illustrative Examples Such services are not widely available, yet sev- eral manufacturing analytics examples prove out the value of data in production environments. For example, Qualityline, an analytics platform sup- plier, claims a 30% improvement in quality and pro- cess efficiency within one year of deployment, illustrating how robust data analytics can materially enhance outputs. Similar insights apply directly to EMS manufacturing environments, where test and inspection data volumes are immense, and the pat- terns can be predictive. Additionally, Altium's Part Analytics solutions promise that EMS companies can optimize sourc- ing and quoting processes. This demonstrates one possible entry point into business transformation through data specific to EMS. Devraj Sathyadevan, a consultant in the EMS, semiconductor, and PCB spaces, writes on how OEM adoption of real-time data and predictive analytics across multiple manufacturing contexts is also well documented as improving operational decision-making for OEMs and EMS companies alike, which simply reinforces the basis for com- mercializing such data. Risks, Challenges, and Mitigation Turning data into a product is not without its risks, of course. First, manufacturing environments often feature heterogeneous systems and inconsistent data standards, which add complexity to the inte- gration process and complicate maintaining clean data, especially across multiple manufacturing sites. Outline good governance practices as you launch the project to reduce the risk of database contamination. Cross-functional collaboration is often challeng- ing, yet it is essential. Adding a customer to the conversation can make it even more challenging. EMS companies should work as cross-functional team members with OEM customers on a daily basis during internal development. When creating solutions tailored to your customers, establish an executive sponsor for each project and make use of the agile model within product teams. As you roll out your data services, OEMs may resist paying for analytics unless the perceived value is clear. Plan ahead during development to understand precise customer pain points this ser- vice will solve and demonstrate measurable busi- ness outcomes to quantify the value added from these services. Conclusion The EMS companies that treat this as a diversifica- tion, transforming operational data into differenti- ated customer value products, such as analytics, predictive insights, API integrations, and structured reporting services, will be the ones to lock in cus- tomers, command premium pricing, and build dura- ble recurring revenue streams. For EMS leadership teams, the path forward requires investing not only in the technologies themselves but also in the organizational, prod- uct management, and go-to-market capabilities needed to monetize data effectively. As OEM cus- tomers demand deeper insight and predictive fore- sight into manufacturing processes, EMS providers that choose to deliver this intelligence as a ser- vice will emerge as winners in 2026 and beyond. SMT007